发布求助
文献互助 智能选刊 最新文献

Journal of Empirical Finance最新文献

筛选
英文 中文
Banker directors on board and corporate tax avoidance 董事会中的银行家董事与公司避税
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-09-08 DOI: 10.1016/j.jempfin.2024.101551
Qian Song , Wenjie Ding , Iftekhar Hasan , Qingwei Wang
{"title":"Banker directors on board and corporate tax avoidance","authors":"Qian Song ,&nbsp;Wenjie Ding ,&nbsp;Iftekhar Hasan ,&nbsp;Qingwei Wang","doi":"10.1016/j.jempfin.2024.101551","DOIUrl":"10.1016/j.jempfin.2024.101551","url":null,"abstract":"<div><p>We investigate how shareholder-debtholder conflict of interest affects the corporate tax avoidance using a unique setting of the affiliated and unaffiliated commercial bankers’ board representation. Consistent with the notion that board representation grants lenders’ access to private information that helps monitor and influence firms’ tax practice, we find that appointments of affiliated banker directors significantly reduce firms’ tax avoidance behavior, while appointing unaffiliated banker directors shows no such effect. The impact of affiliated banker directors on alleviating tax avoidance is stronger among firms with severer conflict of interest between shareholders and debtholders, specifically among firms with weaker corporate governance, higher financial leverage and higher CEO stock ownership.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"79 ","pages":"Article 101551"},"PeriodicalIF":2.1,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142172418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Pooling and winsorizing machine learning forecasts to predict stock returns with high-dimensional data 利用高维数据对机器学习预测进行汇集和胜选，以预测股票回报率
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-09-02 DOI: 10.1016/j.jempfin.2024.101538
Erik Mekelburg , Jack Strauss
{"title":"Pooling and winsorizing machine learning forecasts to predict stock returns with high-dimensional data","authors":"Erik Mekelburg ,&nbsp;Jack Strauss","doi":"10.1016/j.jempfin.2024.101538","DOIUrl":"10.1016/j.jempfin.2024.101538","url":null,"abstract":"<div><p>We evaluate US market return predictability using a novel data set of several hundred ag- gregated firm-level characteristics. We apply LASSO, Elastic Net, Random Forest, Neural Net, Extreme Gradient Boosting, and Light Gradient Boosting Machine methods and find these models experience large prediction errors that lead to forecast failures. However, winsorizing and pooling machine learning model forecasts provides consistent out-of-sample predictability. To assess robustness, we apply machine learning methods to high-dimensional data for Canada, China, Germany and the UK as well as the Goyal–Welch data. All machine learning models we consider, except for the ensemble pooled methods, fail to significantly predict returns across our samples, highlighting the importance of pooling, evaluating additional economies, and the fragility of individual machine learning methods. Our results shed light on the sparsity versus density debate as the degree of sparsity and variable importance evolves over time.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"79 ","pages":"Article 101538"},"PeriodicalIF":2.1,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0927539824000732/pdfft?md5=a9db7e6e4ae641bec07f185220532c35&pid=1-s2.0-S0927539824000732-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Time-varying relative risk aversion: Theoretical mechanism and empirical evidence 时变相对风险规避：理论机制和经验证据
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-09-01 DOI: 10.1016/j.jempfin.2024.101535
Xuan Liu , Haiyong Liu , Zongwu Cai
{"title":"Time-varying relative risk aversion: Theoretical mechanism and empirical evidence","authors":"Xuan Liu ,&nbsp;Haiyong Liu ,&nbsp;Zongwu Cai","doi":"10.1016/j.jempfin.2024.101535","DOIUrl":"10.1016/j.jempfin.2024.101535","url":null,"abstract":"<div><p>This paper explores the issue of understanding time-varying relative risk aversion with household-level data on two classical portfolio choice problems. First, we derive an analytic form solution to a parsimonious portfolio choice model with the preference given by Greenwood, Hercowitz and Huffman (1988, GHH), and then, the solution identifies four partial equilibrium effects in our model with the GHH preference on risky shares through two channels and two net effects whose signs hinge on the value of a key structural parameter. Based on household-level data, our empirical results from both mean and quantile regression models show clearly that wealth negatively affects risky shares and the estimated effects are statistically significant and robust, which is in line with the theory. Finally, we show that the GHH preference alone is not sufficient in explaining how risky shares respond to labor income in the household-level data.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"78 ","pages":"Article 101535"},"PeriodicalIF":2.1,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Mispricing and Anomalies: An Exogenous Shock to Short Selling from JGTRRA 错误定价与异常现象：来自 JGTRRA 的卖空外生冲击
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-09-01 DOI: 10.1016/j.jempfin.2024.101537
Yufeng Han , Yueliang (Jacques) Lu , Weike Xu , Guofu Zhou
{"title":"Mispricing and Anomalies: An Exogenous Shock to Short Selling from JGTRRA","authors":"Yufeng Han ,&nbsp;Yueliang (Jacques) Lu ,&nbsp;Weike Xu ,&nbsp;Guofu Zhou","doi":"10.1016/j.jempfin.2024.101537","DOIUrl":"10.1016/j.jempfin.2024.101537","url":null,"abstract":"<div><p>We investigate the causal impact of short-sale constraints on market anomalies by analyzing a comprehensive set of 182 anomalies. Our approach leverages a persistent, robust, and plausibly exogenous shock to short-selling supply caused by the dividend tax law change in the Job and Growth Tax Relief Reconciliation Act (JGTRRA) of 2003. Our findings reveal that anomalies decline after JGTRRA. However, this tax law change impedes arbitrageurs’ ability to correct mispricing, resulting in anomalies decaying less following dividend record months compared to other months post-JGTRRA. Furthermore, this effect is concentrated on overpriced stocks as opposed to underpriced stocks. Interestingly, while this shock significantly affects most types of anomalies, valuation anomalies remain unaffected.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"78 ","pages":"Article 101537"},"PeriodicalIF":2.1,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142097431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The risk–return tradeoff among equity factors 股票因素之间的风险收益权衡
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-09-01 DOI: 10.1016/j.jempfin.2024.101518
Pedro Barroso , Paulo Maio
{"title":"The risk–return tradeoff among equity factors","authors":"Pedro Barroso ,&nbsp;Paulo Maio","doi":"10.1016/j.jempfin.2024.101518","DOIUrl":"10.1016/j.jempfin.2024.101518","url":null,"abstract":"<div><p>We examine the time-series risk–return tradeoff among equity factors. We obtain a positive tradeoff for profitability and investment factors, which is consistent with the APT. Such relationship subsists when we control by the covariance with the market factor, which represents consistency with Merton’s ICAPM. Critically, we obtain an insignificant risk–return relationship for the market and other factors. The tradeoff is weaker among international equity markets. The out-of-sample forecasting power tends to be economically significant for the investment and profitability factors. Our results suggest that the risk–return tradeoff is stronger within segments of the stock market than for the whole.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"78 ","pages":"Article 101518"},"PeriodicalIF":2.1,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Using the Bayesian sampling method to estimate corporate loss given default distribution 使用贝叶斯抽样法估计违约分布情况下的企业损失
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-08-28 DOI: 10.1016/j.jempfin.2024.101540
Xiaofei Zhang, Xinlei Zhao
{"title":"Using the Bayesian sampling method to estimate corporate loss given default distribution","authors":"Xiaofei Zhang,&nbsp;Xinlei Zhao","doi":"10.1016/j.jempfin.2024.101540","DOIUrl":"10.1016/j.jempfin.2024.101540","url":null,"abstract":"<div><p>We use Markov chain Monte Carlo (MCMC) sampling to draw model coefficients to generate LGD distributions. We find that applying this Bayesian method on a sophisticated model, such as the zero-one-inflated beta (ZOIB) model, that accounts for the bi-modal distribution of the LGDs can generate LGD distributions that mimic the observed distributions well. By contrast, applying this Bayesian sampling approach on a simple model such as Tobit cannot capture the bi-modal LGD distributions accurately. Finally, we argue that this Bayesian sampling approach to generate LGD distributions is better fit for the stress testing purpose than the typical approach to estimate LGD model coefficients and then stress the macro variables. The latter approach yields stressed LGDs that may not be conservative enough, even if the macro variables are stressed to their worst historical values.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"79 ","pages":"Article 101540"},"PeriodicalIF":2.1,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Estimation and inference in low frequency factor model regressions with overlapping observations 有重叠观测数据的低频因子模型回归估计和推论
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-08-23 DOI: 10.1016/j.jempfin.2024.101536
Asad Dossani
{"title":"Estimation and inference in low frequency factor model regressions with overlapping observations","authors":"Asad Dossani","doi":"10.1016/j.jempfin.2024.101536","DOIUrl":"10.1016/j.jempfin.2024.101536","url":null,"abstract":"<div><p>A low frequency factor model regression uses changes or returns computed at a lower frequency than data available. Using overlapping observations to estimate low frequency factor model regressions results in more efficient estimates of OLS coefficients and standard errors, relative to using independent observations or high frequency estimates. I derive the relevant inference and propose a new method to correct for the induced autocorrelation. I present a series of simulations and empirical examples to support the theoretical results. In tests of asset pricing models, using overlapping observations results in lower pricing errors, compared to existing alternatives.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"78 ","pages":"Article 101536"},"PeriodicalIF":2.1,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142088408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Tone or term: Machine-learning text analysis, featured vocabulary extraction, and evidence from bond pricing in China 语气或术语：机器学习文本分析、特色词汇提取以及中国债券定价证据
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-08-22 DOI: 10.1016/j.jempfin.2024.101534
Yueqian Peng , Li Shi , Xiaojun Shi , Songtao Tan
{"title":"Tone or term: Machine-learning text analysis, featured vocabulary extraction, and evidence from bond pricing in China","authors":"Yueqian Peng ,&nbsp;Li Shi ,&nbsp;Xiaojun Shi ,&nbsp;Songtao Tan","doi":"10.1016/j.jempfin.2024.101534","DOIUrl":"10.1016/j.jempfin.2024.101534","url":null,"abstract":"<div><p>We apply the machine-learning technique proposed by Zhou et al. (2024) to analyze credit rating reports in China’s bond markets, identifying featured vocabulary and generating text analysis scores. Compared with the traditional bag-of-words text analysis, evidence suggests three advantages of machine-learning scoring. Firstly, it covers featured vocabulary that compensates for missing information; secondly, it reduces misclassification of words’ sentiments; moreover, it mitigates the problem of equal weighting inherent in the bag-of-words method. Our findings indicate that the featured vocabulary neglected in the bag-of-words method plays a crucial role in text analysis and significantly contributes to bond pricing. Additionally, we find that machine-learning text analysis can address AAA rating inflation within China’s bond markets to some extent. In contrast, the bag-of-words method exhibits limited efficacy in mitigating this issue.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"78 ","pages":"Article 101534"},"PeriodicalIF":2.1,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142048366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Persistent and transient variance components in option pricing models with variance-dependent Kernel 依赖方差核的期权定价模型中的持续方差成分和瞬时方差成分
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-08-22 DOI: 10.1016/j.jempfin.2024.101531
Hamed Ghanbari
{"title":"Persistent and transient variance components in option pricing models with variance-dependent Kernel","authors":"Hamed Ghanbari","doi":"10.1016/j.jempfin.2024.101531","DOIUrl":"10.1016/j.jempfin.2024.101531","url":null,"abstract":"<div><p>This paper examines theoretically and empirically a variance-dependent pricing kernel in the continuous-time two-factor stochastic volatility (SV) model. We investigate the relevance of such a kernel in the joint modeling of index returns and option prices. We contrast the pricing performance of this model in capturing the term structure effects and smile/smirk patterns to discrete-time GARCH models with similar variance-dependent kernels. We find negative and significant risk premium for both volatility factors, implying that investors are willing to pay for insurance against increases in volatility risk, even if it has little persistence. In-sample, the component GARCH model exhibits a slightly better fit overall and across all maturity buckets than the two-factor SV model. However, the two-factor SV model reduces strike price bias, giving rise to the model’s ability in reconciling the physical and risk-neutral distribution. Out-of-sample, the two-factor SV model has better fit to data.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"79 ","pages":"Article 101531"},"PeriodicalIF":2.1,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0927539824000665/pdfft?md5=8487280d2ffab15b3ad43290e53104ee&pid=1-s2.0-S0927539824000665-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The 2008 short-selling ban’s impact on tail risk 2008 年卖空禁令对尾部风险的影响
IF 2.1 2区 经济学
Journal of Empirical Finance Pub Date : 2024-08-20 DOI: 10.1016/j.jempfin.2024.101532
Jonas Bartl , Denefa Bostandzic , Felix Irresberger , Gregor Weiß , Ruomei Yang
{"title":"The 2008 short-selling ban’s impact on tail risk","authors":"Jonas Bartl ,&nbsp;Denefa Bostandzic ,&nbsp;Felix Irresberger ,&nbsp;Gregor Weiß ,&nbsp;Ruomei Yang","doi":"10.1016/j.jempfin.2024.101532","DOIUrl":"10.1016/j.jempfin.2024.101532","url":null,"abstract":"<div><p>We examine how the 2008 U.S. short-selling ban on the stocks of financial institutions impacted their equity tail risk. Using propensity score matching and difference-in-difference regressions, we show that the ban was not effective in restoring financial stability as measured by the stocks’ dynamic Marginal Expected Shortfall. In contrast, especially large institutions, those who were most vulnerable to market downturns in the preban period, as well as those equities with associated put option contracts, experienced sharp increases in their exposure to market downturns during the ban period, contrary to regulators’ intentions.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"78 ","pages":"Article 101532"},"PeriodicalIF":2.1,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0927539824000677/pdfft?md5=84fba35aebc9f925ab99427461c04e0b&pid=1-s2.0-S0927539824000677-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142048361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信